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Analysis of human exposure to landslides with a GIS multiscale approach
ID
Modugno, Sirio
(
Author
),
ID
Johnson, Sarah C. M.
(
Author
),
ID
Borrelli, Pasquale
(
Author
),
ID
Alam, Edris
(
Author
),
ID
Bezak, Nejc
(
Author
),
ID
Balzter, Heiko
(
Author
)
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https://link.springer.com/content/pdf/10.1007/s11069-021-05186-7.pdf
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Abstract
Decision-making plays a key role in reducing landslide risk and preventing natural disasters. Land management, recovery of degraded lands, urban planning, and environmental protection in general are fundamental for mitigating landslide hazard and risk. Here, we present a GIS-based multi-scale approach to highlight where and when a country is affected by a high probability of landslide occurrence. In the first step, a landslide human exposure equation is developed considering the landslide susceptibility triggered by rain as hazard, and the population density as exposed factor. The output, from this overview analysis, is a global GIS layer expressing the number of potentially affected people by month, where the monthly rain is used to weight the landslide hazard. As following step, Logistic Regression (LR) analysis was implemented at a national and local level. The Receiver Operating Characteristic indicator is used to understand the goodness of a LR model. The LR models are defined by a dependent variable, presence–absence of landslide points, versus a set of independent environmental variables. The results demonstrate the relevance of a multi-scale approach, at national level the biophysical variables are able to detect landslide hotspot areas, while at sub-regional level geomorphological aspects, like land cover, topographic wetness, and local climatic condition have greater explanatory power.
Language:
English
Keywords:
disaster risk reduction
,
landslide probability
,
logistic regression
,
landslide trigger factors
,
GIS model
,
global map
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FGG - Faculty of Civil and Geodetic Engineering
Publication status:
Published
Publication version:
Version of Record
Publication date:
10.01.2022
Year:
2022
Number of pages:
[26] f.
Numbering:
Vol. 10. jan.
PID:
20.500.12556/RUL-135500
UDC:
502/504:55
ISSN on article:
0921-030X
DOI:
10.1007/s11069-021-05186-7
COBISS.SI-ID:
93500419
Publication date in RUL:
16.03.2022
Views:
725
Downloads:
115
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Record is a part of a journal
Title:
Natural hazards
Shortened title:
Nat. hazards
Publisher:
Kluwer Academic Pubishers
ISSN:
0921-030X
COBISS.SI-ID:
9844229
Secondary language
Language:
Slovenian
Keywords:
zmanjševanje tveganja
,
plazovi
,
regresija
,
sprožitveni dejavniki
,
GIS
,
globalna karta
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